• DocumentCode
    1796603
  • Title

    VM scheduling strategies based on artificial intelligence in Cloud Testing

  • Author

    Yang Zheng ; Lizhi Cai ; Shidong Huang ; Zhihong Wang

  • Author_Institution
    Sch. of Inf. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2014
  • fDate
    June 30 2014-July 2 2014
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Virtualization technology not only is the basis of Cloud computing technology, but also plays an important role in Cloud Testing. Cloud Testing takes advantage of virtualization technology to generate VM (virtual machine) resources in the physical machine, and adopts the corresponding strategies to schedule the VM resources. VM scheduling strategies have a crucial impact on the overall performance of Cloud Testing. The paper first introduces the scheduling process of VM in Cloud Testing, and divides the common scheduling strategies into three categories: center on saving energy, center on load balancing and center on Qos performance. Then the common VM scheduling strategies in current Cloud Testing environment are analyzed. Finally, their advantages and disadvantages are also discussed.
  • Keywords
    artificial intelligence; cloud computing; program testing; virtual machines; Qos performance; VM resources; VM scheduling strategies; artificial intelligence; cloud computing technology; cloud testing; load balancing; saving energy; virtual machine; virtualization technology; Cloud computing; Genetic algorithms; Load management; Processor scheduling; Quality of service; Scheduling; Testing; Cloud Testing; Cloud computing; VM; Virtual Machine scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2014 15th IEEE/ACIS International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/SNPD.2014.6888746
  • Filename
    6888746